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  1. Stackups
  2. Application & Data
  3. Container Registry
  4. Container Tools
  5. Docker Machine vs Kubernetes

Docker Machine vs Kubernetes

OverviewDecisionsComparisonAlternatives

Overview

Kubernetes
Kubernetes
Stacks61.2K
Followers52.8K
Votes685
Docker Machine
Docker Machine
Stacks430
Followers518
Votes12

Docker Machine vs Kubernetes: What are the differences?

Introduction

In this task, we will discuss the key differences between Docker Machine and Kubernetes.

1. Docker Machine: Docker Machine is a tool that helps in creating and managing multiple Docker hosts. It enables users to install Docker Engine on various host platforms, including local machines, cloud providers, and virtual machines. Docker Machine simplifies the process of creating and managing Docker environments on different hosts, allowing users to work seamlessly with containers.

2. Kubernetes: Kubernetes, on the other hand, is a powerful container orchestration platform. It is designed to automate the management, scaling, and deployment of containerized applications. Kubernetes provides a container-centric infrastructure that allows developers to manage containers across multiple hosts efficiently. It offers features like high availability, auto-scaling, rolling updates, load balancing, and more.

3. Docker Machine's Purpose: Docker Machine primarily focuses on managing individual Docker hosts and creating Docker environments that can run containers. It provides a simple way to set up and manage Docker on various host platforms, making it easy for developers to deploy containers locally or on remote machines. Docker Machine is suitable for small-scale deployments or when working with a single host.

4. Kubernetes' Purpose: Kubernetes, on the other hand, is designed to manage containerized applications at scale. It abstracts the underlying infrastructure and provides a layer of orchestration and automation. Kubernetes enables users to manage and deploy applications across a cluster of multiple hosts, allowing organizations to scale their containerized applications efficiently.

5. Level of Abstraction: Docker Machine operates at a lower level of abstraction compared to Kubernetes. It focuses on managing individual Docker hosts and their environments. Docker Machine allows developers to create and manage Docker machines using a command-line interface. On the other hand, Kubernetes operates at a higher level of abstraction by providing a platform to manage containerized applications without worrying about the underlying host infrastructure.

6. Scalability and Cluster Management: One of the key differences between Docker Machine and Kubernetes is their approach to scalability and cluster management. Docker Machine is not specifically designed for scaling containerized applications across multiple hosts. It is more suitable for managing individual hosts or small-scale deployments. On the other hand, Kubernetes excels at managing clusters of hosts and scaling applications across them. It provides features like automatic load balancing, self-healing, and horizontal scaling, making it ideal for large-scale deployments.

In summary, Docker Machine is a tool for managing Docker hosts and environments, while Kubernetes is a powerful container orchestration platform designed for scaling and managing containerized applications across clusters of hosts. Docker Machine operates at a lower level of abstraction and is suitable for smaller deployments, while Kubernetes operates at a higher level of abstraction and excels at managing clusters and large-scale deployments.

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Advice on Kubernetes, Docker Machine

Simon
Simon

Senior Fullstack Developer at QUANTUSflow Software GmbH

Apr 27, 2020

DecidedonGitHubGitHubGitHub PagesGitHub PagesMarkdownMarkdown

Our whole DevOps stack consists of the following tools:

  • @{GitHub}|tool:27| (incl. @{GitHub Pages}|tool:683|/@{Markdown}|tool:1147| for Documentation, GettingStarted and HowTo's) for collaborative review and code management tool
  • Respectively @{Git}|tool:1046| as revision control system
  • @{SourceTree}|tool:1599| as @{Git}|tool:1046| GUI
  • @{Visual Studio Code}|tool:4202| as IDE
  • @{CircleCI}|tool:190| for continuous integration (automatize development process)
  • @{Prettier}|tool:7035| / @{TSLint}|tool:5561| / @{ESLint}|tool:3337| as code linter
  • @{SonarQube}|tool:2638| as quality gate
  • @{Docker}|tool:586| as container management (incl. @{Docker Compose}|tool:3136| for multi-container application management)
  • @{VirtualBox}|tool:774| for operating system simulation tests
  • @{Kubernetes}|tool:1885| as cluster management for docker containers
  • @{Heroku}|tool:133| for deploying in test environments
  • @{nginx}|tool:1052| as web server (preferably used as facade server in production environment)
  • @{SSLMate}|tool:2752| (using @{OpenSSL}|tool:3091|) for certificate management
  • @{Amazon EC2}|tool:18| (incl. @{Amazon S3}|tool:25|) for deploying in stage (production-like) and production environments
  • @{PostgreSQL}|tool:1028| as preferred database system
  • @{Redis}|tool:1031| as preferred in-memory database/store (great for caching)

The main reason we have chosen Kubernetes over Docker Swarm is related to the following artifacts:

  • Key features: Easy and flexible installation, Clear dashboard, Great scaling operations, Monitoring is an integral part, Great load balancing concepts, Monitors the condition and ensures compensation in the event of failure.
  • Applications: An application can be deployed using a combination of pods, deployments, and services (or micro-services).
  • Functionality: Kubernetes as a complex installation and setup process, but it not as limited as Docker Swarm.
  • Monitoring: It supports multiple versions of logging and monitoring when the services are deployed within the cluster (Elasticsearch/Kibana (ELK), Heapster/Grafana, Sysdig cloud integration).
  • Scalability: All-in-one framework for distributed systems.
  • Other Benefits: Kubernetes is backed by the Cloud Native Computing Foundation (CNCF), huge community among container orchestration tools, it is an open source and modular tool that works with any OS.
12.8M views12.8M
Comments
Anis
Anis

Founder at Odix

Nov 7, 2020

Review

I recommend this : -Spring reactive for back end : the fact it's reactive (async) it consumes half of the resources that a sync platform needs (so less CPU -> less money). -Angular : Web Front end ; it's gives you the possibility to use PWA which is a cheap replacement for a mobile app (but more less popular). -Docker images. -Kubernetes to orchestrate all the containers. -I Use Jenkins / blueocean, ansible for my CI/CD (with Github of course) -AWS of course : u can run a K8S cluster there, make it multi AZ (availability zones) to be highly available, use a load balancer and an auto scaler and ur good to go. -You can store data by taking any managed DB or u can deploy ur own (cheap but risky).

You pay less money, but u need some technical 2 - 3 guys to make that done.

Good luck

115k views115k
Comments
Michael
Michael

CEO at asencis Ltd

Jan 5, 2021

Needs advice

We develop rapidly with docker-compose orchestrated services, however, for production - we utilise the very best ideas that Kubernetes has to offer: SCALE! We can scale when needed, setting a maximum and minimum level of nodes for each application layer - scaling only when the load balancer needs it. This allowed us to reduce our devops costs by 40% whilst also maintaining an SLA of 99.87%.

272k views272k
Comments

Detailed Comparison

Kubernetes
Kubernetes
Docker Machine
Docker Machine

Kubernetes is an open source orchestration system for Docker containers. It handles scheduling onto nodes in a compute cluster and actively manages workloads to ensure that their state matches the users declared intentions.

Machine lets you create Docker hosts on your computer, on cloud providers, and inside your own data center. It creates servers, installs Docker on them, then configures the Docker client to talk to them.

Lightweight, simple and accessible;Built for a multi-cloud world, public, private or hybrid;Highly modular, designed so that all of its components are easily swappable
-
Statistics
Stacks
61.2K
Stacks
430
Followers
52.8K
Followers
518
Votes
685
Votes
12
Pros & Cons
Pros
  • 166
    Leading docker container management solution
  • 130
    Simple and powerful
  • 108
    Open source
  • 76
    Backed by google
  • 58
    The right abstractions
Cons
  • 16
    Steep learning curve
  • 15
    Poor workflow for development
  • 8
    Orchestrates only infrastructure
  • 4
    High resource requirements for on-prem clusters
  • 2
    Too heavy for simple systems
Pros
  • 12
    Easy docker hosts management
Integrations
Vagrant
Vagrant
Docker
Docker
Rackspace Cloud Servers
Rackspace Cloud Servers
Microsoft Azure
Microsoft Azure
Google Compute Engine
Google Compute Engine
Ansible
Ansible
Google Kubernetes Engine
Google Kubernetes Engine
Docker
Docker

What are some alternatives to Kubernetes, Docker Machine?

Rancher

Rancher

Rancher is an open source container management platform that includes full distributions of Kubernetes, Apache Mesos and Docker Swarm, and makes it simple to operate container clusters on any cloud or infrastructure platform.

Docker Compose

Docker Compose

With Compose, you define a multi-container application in a single file, then spin your application up in a single command which does everything that needs to be done to get it running.

Docker Swarm

Docker Swarm

Swarm serves the standard Docker API, so any tool which already communicates with a Docker daemon can use Swarm to transparently scale to multiple hosts: Dokku, Compose, Krane, Deis, DockerUI, Shipyard, Drone, Jenkins... and, of course, the Docker client itself.

Tutum

Tutum

Tutum lets developers easily manage and run lightweight, portable, self-sufficient containers from any application. AWS-like control, Heroku-like ease. The same container that a developer builds and tests on a laptop can run at scale in Tutum.

Portainer

Portainer

It is a universal container management tool. It works with Kubernetes, Docker, Docker Swarm and Azure ACI. It allows you to manage containers without needing to know platform-specific code.

Codefresh

Codefresh

Automate and parallelize testing. Codefresh allows teams to spin up on-demand compositions to run unit and integration tests as part of the continuous integration process. Jenkins integration allows more complex pipelines.

CAST.AI

CAST.AI

It is an AI-driven cloud optimization platform for Kubernetes. Instantly cut your cloud bill, prevent downtime, and 10X the power of DevOps.

k3s

k3s

Certified Kubernetes distribution designed for production workloads in unattended, resource-constrained, remote locations or inside IoT appliances. Supports something as small as a Raspberry Pi or as large as an AWS a1.4xlarge 32GiB server.

Flocker

Flocker

Flocker is a data volume manager and multi-host Docker cluster management tool. With it you can control your data using the same tools you use for your stateless applications. This means that you can run your databases, queues and key-value stores in Docker and move them around as easily as the rest of your app.

Kitematic

Kitematic

Simple Docker App management for Mac OS X

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